We firstly present our results on the Aishell-1 test dataset to provide a deep insight into our method. The effectiveness of the proposed method is further verified on the larger corpus (1400-hours internal corpus).
To evaluate the effectiveness of the two Blockformer methods Base-WSBO and SE-WSBO, we conduct some experiments to compare differences. The performance of the models is evaluated based on character error rates (CERs) both without and with external language models. All our experimental results are based on the attention-rescore two-step decoding method [1]}, [2]}.
